Heart Beat Research Articles

Molecular mechanisms of metabolic dysregulation in diabetic cardiomyopathy.

Diabetic cardiomyopathy (DCM), one of the most serious complications of diabetes mellitus, has become recognized as a cardiometabolic disease. In normoxic conditions, the majority of the ATP production (>95%) required for heart beating comes from mitochondrial oxidative phosphorylation of fatty acids (FAs) and glucose, with the remaining portion coming from a variety of sources, including fructose, lactate, ketone bodies (KB) and branched chain amino acids (BCAA). Increased FA intake and decreased utilization of glucose and lactic acid were observed in the diabetic hearts of animal models and diabetic patients. Moreover, the polyol pathway is activated, and fructose metabolism is enhanced. The use of ketones as energy sources in human diabetic hearts also increases significantly. Furthermore, elevated BCAA levels and impaired BCAA metabolism were observed in the hearts of diabetic mice and patients. The shift in energy substrate preference in diabetic hearts results in increased oxygen consumption and impaired oxidative phosphorylation, leading to diabetic cardiomyopathy. However, the precise mechanisms by which impaired myocardial metabolic alterations result in diabetes mellitus cardiac disease are not fully understood. Therefore, this review focuses on the molecular mechanisms involved in alterations of myocardial energy metabolism. It not only adds more molecular targets for the diagnosis and treatment, but also provides an experimental foundation for screening novel therapeutic agents for diabetic cardiomyopathy.

Application of Liquid Chromatography Coupled to Mass Spectrometry for Direct Estimation of the Total Levels of Adenosine and Its Catabolites in Human Blood.

Adenosine is a multifunctional nucleoside with several roles across various levels in organisms. Beyond its intracellular involvement in cellular metabolism, extracellular adenosine potently influences both physiological and pathological processes. In relation to its blood level, adenosine impacts the cardiovascular system, such as heart beat rate and vasodilation. To exploit the adenosine levels in the blood, we employed the liquid chromatography method coupled with mass spectrometry (LC-MS). Immediately after collection, a blood sample mixed with acetonitrile solution that is either enriched with 13C-labeled adenosine or a newly generated mixture is transferred into the tubes containing the defined amount of 13C-labeled adenosine. The 13C-enriched isotopic adenosine is used as an internal standard, allowing for more accurate quantification of adenosine. This novel protocol for LC-MS-based estimation of adenosine delivers a rapid, highly sensitive, and reproducible means for quantitative estimation of total adenosine in blood. The method also allows for quantification of a few catabolites of adenosine, i.e., inosine, hypoxanthine, and xanthine. Our current setup did not allow for the detection or quantifying of uric acid, which is the final product of adenosine catabolism. This advancement provides an analytical tool that has the potential to enhance our understanding of adenosine's systemic impact and pave the way for further investigations into its intricate regulatory mechanisms.

Classifying Abnormalities In Heart Beat Sound

Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure. in an early stage. In the proposed method various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (Melfrequency cepstral coefficients). Then, a Deep Learning Approach is applied in which the MFCC audio signals are sent to the CNN (Convolutional Neural Network) + LSTM (Long Short-Term Memory) model to extract and classify the abnormal heartbeat sounds with its associated disease. Thus, a system for classifying abnormal heartbeat sounds is proposed by leading a way to identify and diagnose diseases that are identified using heartbeat sounds in an early stage.

Sex differences in sympathetic activity and pulse wave velocity in adults with chronic kidney disease.

Chronic kidney disease (CKD) is characterized by sympathetic nervous system (SNS) overactivity that contributes to increased vascular stiffness and cardiovascular risk. Although it is well established that SNS activity and vascular stiffness are substantially elevated in CKD, whether sex differences in autonomic and vascular function exist in CKD remains unknown. We tested the hypothesis that compared with females, males with CKD have higher baseline sympathetic activity that is related to increased arterial stiffness. One hundred twenty-nine participants (96 males and 33 females) with CKD stages III and IV were recruited and enrolled. During two separate study visits, vascular stiffness was assessed by measuring carotid-to-femoral pulse wave velocity (cfPWV), and resting muscle sympathetic nerve activity (MSNA) was measured by microneurography. Males with CKD had higher resting MSNA compared with females with CKD (68 ± 16 vs. 55 ± 14 bursts/100 heart beats, P = 0.005), whereas there was no difference in cfPWV between the groups (P = 0.248). Resting MSNA was not associated with cfPWV in both males and females. In conclusion, males with CKD have higher resting sympathetic activity compared with females with CKD. However, there was no difference in vascular stiffness between the sexes. There was no correlation between resting MSNA and cfPWV, suggesting that non-neural mechanisms may play a greater role in the progression of vascular stiffness in CKD, particularly in females.NEW & NOTEWORTHY Males with chronic kidney disease (CKD) have higher resting muscle sympathetic nerve activity (MSNA) compared with females. There was no correlation between MSNA and carotid-to-femoral pulse wave velocity (cfPWV), suggesting that non-neural mechanisms may play a greater role in the progression of vascular stiffness in CKD. Sex differences in SNS activity may play a mechanistic role in observations from epidemiological studies suggesting greater cardiovascular risk in males compared with females with CKD.

Comparison of bupivacaine and levobupivacaine in continuous axillary brachial plexus block

Aims: This study compares bupivacaine – lidocaine and levobupivacaine – lidocaine administrations in terms of initiation and duration of motor and sensorial blockage, total number of additional analgesic applications, analgesic amount consumed in 24 hours, side-effects and hemodynamic effects in continuous axillary brachial pleksus block in hand and forearm surgery. Methods: Thirty ASA I & II physical status patients, scheduled hand or forearm surgery were enrolled for of the two groups in a randomized study. Axillary catheter duly placed in both group with appropriate guided techniques. Patients in group B received 0. 5% bupivacaine 20 ml + 2% lidocaine 20 ml and group L received 0. 5% levobupivacaine 20 ml + 2% lidocaine 20 ml through the axillary catheter. Initiation and duration of motor and sensorial block, total number of additional analgesic applications and analgesic amount consumed in postoperative 24 hours were recorded. Pre-block, peri-operative and post-operative blood pressures and heart beat rates were also recorded. Block application duration, operation duration, tourniquet duration and demographic data of patients (age, sex, weight, and length) were recorded. Demanded and applied analgesic doses by the patient controlled analgesia devices, side effects and complications were also recorded. Results: There was no statistically significant difference between two groups in terms of initiation and duration of motor and sensorial block, amount of analgesic consumed in 24 hours, demanded and applied analgesic doses by the patient controlled analgesia devices and hemodynamic data (p>0. 05). There is a mild and positive relation between block application duration and patient weight. (p=0. 014; r=0. 444) Conclusion: Both bupivacaine+lidocaine and levobupivacaine+lidocaine combinations can safely be used in axillary continuous brachial plexus block without any difference in terms of initiation and duration of block, total analgesic amount consumed. Their duration of action and effect on hemodynamic responses are similar.

Emergency Surgical Management of Thoracic and Limb Injuries in a Hare (Lepus nigricollis)

A one-month old hare (Lepus nigricollis) was brought to the department in emergency with a complaint of dog bite two hours ago due to long chase with dog. Animal was unconscious due to numerous wounds on the thorax and limbs. On clinical examination, fast heart beats were measured from the thoracic perforation at 5th intercostal space and an open wound at the hock joint with abrasions was visible on right hind limb. The animal was handled with appropriate care and after stabilization of vital parameters, surgical management was undertaken under general anaesthesia. The animal showed marked improvement and recovered uneventfully on the 10th post-operative day.

STANet: Spatio-Temporal Adaptive Network and Clinical Prior Embedding Learning for 3D+T CMR Segmentation.

The segmentation of cardiac structure in magnetic resonance images (CMR) is paramount in diagnosing and managing cardiovascular illnesses, given its 3D+Time (3D+T) sequence. The existing deep learning methods are constrained in their ability to 3D+T CMR segmentation, due to: (1) Limited motion perception. The complexity of heart beating renders the motion perception in 3D+T CMR, including the long-range and cross-slice motions. The existing methods' local perception and slice-fixed perception directly limit the performance of 3D+T CMR perception. (2) Lack of labels. Due to the expensive labeling cost of the 3D+T CMR sequence, the labels of 3D+T CMR only contain the end-diastolic and end-systolic frames. The incomplete labeling scheme causes inefficient supervision. Hence, we propose a novel spatio-temporal adaptation network with clinical prior embedding learning (STANet) to ensure efficient spatio-temporal perception and optimization on 3D+T CMR segmentation. (1) A spatio-temporal adaptive convolution (STAC) treats the 3D+T CMR sequence as a whole for perception. The long-distance motion correlation is embedded into the structural perception by learnable weight regularization to balance long-range motion perception. The structural similarity is measured by cross-attention to adaptively correlate the cross-slice motion. (2) A clinical prior embedding learning strategy (CPE) is proposed to optimize the partially labeled 3D+T CMR segmentation dynamically by embedding clinical priors into optimization. STANet achieves outstanding performance with Dice of 0.917 and 0.94 on two public datasets (ACDC and STACOM), which indicates STANet has the potential to be incorporated into computer-aided diagnosis tools for clinical application.

Morphological and Elemental Analysis of Cyathulaprostrata (L.) Blume using Atomic Absorption Spectroscopy

Cyathulaprostrata (L.) Blume. is a herb or under shrubs belongs to the family Amaranthaceae. It grows in loamy and sandy soils. It is commonly called small prickly chaff flower or pastures weed. It is used as a medicinal plant as well as food. The present study includes the morphological and elemental analysis of Cyathulaprostrata (L.) Blume. Cyathulaprostrata (L.) Blume consist of opposite, petiolate and entire leaves, with very small hermaphrodite flowers with bracts and bracteoles. The inflorescence is a raceme or a spike. The perianth of perfect flowers are scarious and five lobed. It has five stamens with filaments connate at the base. It has two celled anthers, obovoid and one celled ovary with a solitary ovule, simple style with capitulate stigma. The fruit is a membranous utricle enclosed in a perianth. The elemental composition of Cyathulaprostrata (L.) Blume. Leaves have been determined by using atomic absorption spectroscopy. Elements such as Ca2+, Fe2+, Mg2+, Mn2+, Na2+, Zn2+, Cd2+, Cr2+, Pb2+, Ni2+, Cu2+, Ag2+ were determined. The result of analysis showed that calcium has the highest concentration, which helps to build bones and keeps them healthy and also helps in blood clotting, muscle contraction, heart beat etc. The plant also contains other essential elements like iron, magnesium, manganese etc. The toxic metals like lead and cadmium also present in trace amount. The purpose of this study is to analyze the morphology, pharmacological potential and composition of elements in Cyathulaprostrata (L.)Blume.

Beating Heart Transplantation: How to Do It.

Heart transplantation utilizing deceased after circulatory death (DCD) donors has expanded the donor pool through the use of ex vivo normothermic perfusion. Compared with brain death donation, the conventional method of performing DCD heart transplantation includes an additional period of warm and cold ischemia. We have developed a beating heart implantation technique that obliviates the need for a second cardioplegic arrest and the associated reperfusion injury. We hypothesize this reproducible method may improve short-term and long-term outcomes to mirror results seen in brain death donors and provide details on how to perform beating heart transplantation.

Assessment of cardiac arrhythmias, P wave and QT dispersion in systemic sclerosis

Cardiac involvement in systemic sclerosis (SSc) is significant cause of SSc-related mortality. The objective of the study was to assess cardiac arrhythmias, P wave and QT dispersion in SSc patients. 40 SSc patients and 40 healthy participants who had similar sociodemographic characteristics with the patients were enrolled in the study. P wave dispersion (Pd), QT dispersion (QTd), and corrected QT (QTc) dispersion (QTcd) were calculated by measuring maximum (max) and minimum (min) of P wave, QT interval, QTc in 12-leads electrocardiography (ECG). Cardiac arrhythmias and conduction disorders were assessed by ECG and Holter-ECG. The mean age of SSc patients (92.5% of females) was 50.9±13.9 years similar with the healthy group (51.4±8.9). Abnormal ECG findings were found in 27.5% of SSc patients and remarkably higher in comparison to the healthy participants (p=0.019). The most frequently reported abnormal ECG findings were left anterior fascicular block (15%), ventricular premature beat (10%) and first-degree atrioventricular heart block (5%). The comparison of dispersion showed no statistically important difference in Pd between two groups (p=0.69) while QTd, QTc, QTcd, QTc min, and QTc max were markedly prolonged in patients with SSc (p=0.039; p<0.001; p=0.021; p<0.001; p<0.001, respectively). The assessment of Holter-ECG demonstrated that supraventricular tachycardia was frequently detected in patients with SSc (22.5% vs 2.5%; p=0.007). This study indicated a significantly elevated incidence of abnormal ECG results and SVT, an arrhythmia not typically identifiable through standard ECG but detectable via Holter monitoring, in patients with SSc. In the study, QTd, QTc, and QTcd intervals were significantly longer in SSc patients, which may indicate a susceptibility to arrhythmias.

Clinical Characteristics and Features of Idiopathic Premature Ventricular Contractions with an Enlarged Left Atrium in Patients Without Structural Heart Diseases

Background and aims: Idiopathic premature ventricular contractions (PVCs) may cause subtle changes in left atrium (LA) structure and function. Here, we investigated whether serum sodium, body mass index (BMI), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and other characteristics might be associated with LA in these patients. Methods: A total of 268 consecutive patients diagnosed with idiopathic PVCs were retrospectively analyzed. We assessed associations of enlarged LA and with the clinical features obtained from 24-hour Holter monitoring, electrocardiography and serum data in patients with PVCs. Results: Patients with an enlarged LA (n = 101), compared with a normal LA (n = 167), had significantly lower serum sodium (140.9 ± 3.0 mmol/L vs 141.7 ± 2.8 mmol/L; P = 0.022), higher BMI (24.5 ± 2.7 kg/m2 vs 21.7 ± 2.5 kg/m2; P < 0.001), higher NT-proBNP [99.3 (193.6) pg/mL vs 77.8 (68.8) pg/mL; P < 0.001] and lower average heart rates (73.0 ± 8.0 bpm vs 75.3 ± 7.6 bpm; P = 0.019). No significant differences were observed in P-wave dispersion, QRS duration, PVC coupling interval, pleomorphism, circadian rhythm, non-sustained ventricular tachycardia, serum potassium, serum magnesium, hypersensitive C-reactive protein, low-density lipoprotein cholesterol, symptoms and PVC duration. Conclusions: Beyond the burden of PVCs, attributes such as serum sodium, BMI, NT-proBNP and average heart beats may potentially correlate with LA enlargement in individuals with idiopathic PVCs.

Simulation of heart beat interval series - a neurophysiology based model in comparison with a nonlinear network oscillator model

Simulation of heart beat interval series - a neurophysiology based model in comparison with a nonlinear network oscillator model

An RNN-Bi LSTM Based Multi Decision GAN Approach for the Recognition of Cardiovascular Disease (CVD) From Heart Beat Sound: A Feature Optimization Process

An RNN-Bi LSTM Based Multi Decision GAN Approach for the Recognition of Cardiovascular Disease (CVD) From Heart Beat Sound: A Feature Optimization Process

Healthcare Data Security in Cloud Storage Using Light Weight Symmetric Key Algorithm

Now-a-days, healthcare monitoring system is very much important system in the medical field to know the patient‘s health status immediately. In the proposed system, the sensors are fixed over the patient’s body or placed at some distances around the body to collect patient’s significant parameters like blood pressure, temperature, heart beat rate, etc. These parameters are collected by the healthcare professionals through some connectivity mechanisms like Bluetooth, ZigBee, etc. These significant data will be outsourced to the cloud storage in a secure way to avoid attack from the attackers. So, we need some protection mechanism to safeguard this information. This article proposes a light weight cryptographic algorithm (symmetric key) via random number key generation using Diffie-Hellman key exchange based on Elliptic Curve (ECDH) cryptography. As a result of substituting bytes (S-box) and folding (horizontal and vertical) operations, the proposed symmetric key algorithm achieves the foremost properties of cryptography such as confusion and diffusion quite well. Experimental results showed that the overall execution time of the proposed algorithm is superior to the standard Advanced Encryption Standard (AES) algorithm. The throughput rate of the proposed algorithm is 20.525095 KB/seconds whereas for the standard AES algorithm throughput rate is 18.727215 KB/seconds. So, the proposed algorithm is faster than the existing AES algorithm. Moreover, the construction of S-box, IS-box and the key generation procedures are entirely different in the proposed algorithm so, it increases the complexity for the attacker and it will create confusion to the attacker

Factors associated with gait efficiency in children with cerebral palsy: association between gait abnormality and balance ability.

[Purpose] Children with cerebral palsy require more gait energy than healthy children. The association between gait abnormalities and gait efficiency remains unclear. We investigated the association between gait abnormalities, balance, and maximum step length to determine contributors to gait efficiency in children with cerebral palsy. [Participants and Methods] The study included 33 patients with cerebral palsy, who could walk without the use of walking aids. All participants were instructed to walk for 6 min, and the Total Heart Beat Index was calculated as a measure of walking efficiency. The Edinburgh Visual Gait Score was used to assess gait abnormalities. Additionally, the maximum step length was recorded, and all participants performed the Berg Balance Scale. Correlation analysis and stepwise multiple regression analysis were used to confirm the association between the aforementioned parameters and the Total Heart Beat Index. [Results] The Edinburgh Visual Gait Score was correlated with the heel lift during the stance, knee position during the terminal swing of gait as factors associated with the Total Heartbeat Index. The Berg Balance Scale was correlated with turning 360°, standing with feet together. [Conclusion] Our findings emphasize the need for treatment strategies focused on gait abnormalities and balance.

From Intonation Adjustments to Synchronization of Heart Rate Variability: Singer Interaction in Traditional Georgian Vocal Music

This paper is concerned with how singers of Georgian traditional vocal music interact when singing together. Applying a variety of computational methods from audio signal processing and music information retrieval (MIR), we examine three existing corpora of (field) recordings for manifestations of a high degree of mutual coordination of the singers’ voices. We find numerous examples of harmonically controlled mutual intonation adjustments on both short and long time scales. Furthermore, we believe that the observed differences in melodic and harmonic scales can also be interpreted as (side) effects of the singers’ interaction with the possible goal of achieving harmonic togetherness (or consonance) on the time scale of individual (important) notes. In addition, together with the ensemble Khelkhvavi from Ozurgeti, we conducted an experiment demonstrating the synchronization of singers’ heartbeat rates during the performance of the Gurian song Chven Mshvidoba. The results of our analysis show that a variety of measurable signs of interaction between singers can be observed and documented in existing corpora of Georgian traditional vocal music. Our experience also shows that relevant information about the synchronization of the bodily functions of singers during performances can nowadays be obtained with reasonable technical and logistical effort even in a ‘real world’ framework, thereby allowing us to address questions related to the ‘ecological validity’ of this kind of measurement.

Pilot Randomized Controlled Trial of Multi-Disciplinary Community-Based Biofeedback Vs Health Promotion Programs on Mental Health And Drug Use Among People Experiencing Homelessness

Background: PEH are most vulnerable to COVID-19 due to high levels of chronic disease and social isolation. However, in Skid Row Los Angeles, there are limited resources for mental health and drug treatment services. Biofeedback (BF) has been found to decrease depression and substance use among drug users; however, no studies have assessed the impact of BF on PEH during the COVID-19 pandemic.
 Aim: Our multi-disciplinary team designed and pilot tested an 8-week Heart Rate Variability-Biofeedback (HRV-BF) intervention, utilizing a nurse-led, Community Health Worker model of care with 50 people experiencing homelessness (PEH) as compared with a Health Promotion (HP) program. Our goal was to establish feasibility of the program, and to assess effects HRV-BF on measures of HRV, mental health and drug use as compared to HP.
 Methods: Utilizing Community Based Participatory Research (CBPR) principles, a community advisory board was established to refine the HRV-BF intervention and assess acceptability and feasibility. We enrolled 40 PEH and randomized into HRV-BF vs HP program and assessed a) impact on anxiety and depression; b) HRV and cortisol indices; and c) drug and alcohol use among all participants.
 Results: In total, 40 PEH were enrolled with 36 completing the intervention; 17 HRV-BF and 19 HP. Majority were male (80%) and were equally Black (37.5%) or Hispanic (35%). The mean age of PEH was 49 (SD 16.7), median age 53. The HRV measure RMSSD (root mean square of successive differences between normal heart beats, a time-based variable reflecting vagally mediated HRV), assessed during the resting 5-minute period, showed significant increases in 71% of participants (75% among HRV-BF and 68% among HP), using paired t-tests with natural log transformed variables, p=0.004, and by non-parametric tests, p= 0.006 (p values one-sided). Across the sample, PHQ-9 (depressive symptoms) showed marginally significant improvement (p= 0.09). Anxiety and Mental Health Inventory scores showed improvement, though not significant. Between-group analysis showed the HRV-BF group had better GAD-7 and MHI scores at 8 weeks (post-intervention), though not statistically significant. Chronic disease was found to be high in both groups (67% among HRV-BF and 82% among HP). No significant differences were found in terms of substance use.
 Conclusions: As the first known study to date examining the role of a biofeedback self-regulation training on biomarkers of stress/mental health measures among PEH, our study shows feasibility and acceptability among the study population and positive initial results for both arms of the study. We plan to extend the follow-up period beyond the intervention period of 8 weeks to establish the sustainability of the intervention.
 Funding: Susan Samueli Integrative Health Institute Pilot Studies Award

Design of human heartbeat monitoring system based on wireless sensor networks

The IoT technology plays an important role in Industry 4.0 revolution. The IoT technology has potential to be implemented in the medical industry, especially for the development of telemedicine system. IoT able to send the medical sensor data wirelessly to the nearest medical facility like hospital. In this research, the author designed the heart beat monitoring system by using 802.11 communication protocol and simple web interface. The pulse sensor that used in this research was able to read the pulse rate of the human and convert it to BPM (beat per minute). It has 98.89% accuracy and 1.11% error compared to the smartwatch result. In the other hand, ESP-32 also implemented as the microcontroller as well as the sensor node of the system. It was able to send the data wirelessly from sensor node to the coordinator node. The coordinator node was also able to fetch the sensor data into the database using POST and GET method and then visualize the sensor data over web interface so the other users are able to see the visualization of the sensor data.

Metabolomic and lipidomic landscape of porcine kidney associated with kidney perfusion in heart beating donors and donors after cardiac death

Transplant centers are currently facing a lack of tools to ensure adequate evaluation of the quality of the available organs, as well as a significant shortage of kidney donors. Therefore, efforts are being made to facilitate the effective use of available organs and expand the donor pool, particularly with expanded criteria donors. Fulfilling a need, we aim to present an innovative analytical method based on solid-phase microextraction (SPME) - chemical biopsy. In order to track changes affecting the organ throughout the entire transplant procedure, porcine kidneys were subjected to multiple samplings at various time points. The application of small-diameter SPME probes assured the minimal invasiveness of the procedure. Porcine model kidney autotransplantation was executed for the purpose of simulating two types of donor scenarios: donors with a beating heart (HBD) and donors after cardiac death (DCD). All renal grafts were exposed to continuous normothermic ex vivo perfusion. Following metabolomic and lipidomic profiling using high-performance liquid chromatography coupled to a mass spectrometer, we observed differences in the profiles of HBD and DCD kidneys. The alterations were predominantly related to energy and glucose metabolism, and differences in the levels of essential amino acids, purine nucleosides, lysophosphocholines, phosphoethanolamines, and triacylglycerols were noticed. Our results indicate the potential of implementing chemical biopsy in the evaluation of graft quality and monitoring of renal function during perfusion.

ORRN: An ODE-Based Recursive Registration Network for Deformable Respiratory Motion Estimation With Lung 4DCT Images.

Deformable Image Registration (DIR) plays a significant role in quantifying deformation in medical data. Recent Deep Learning methods have shown promising accuracy and speedup for registering a pair of medical images. However, in 4D (3D + time) medical data, organ motion, such as respiratory motion and heart beating, can not be effectively modeled by pair-wise methods as they were optimized for image pairs but did not consider the organ motion patterns necessary when considering 4D data. This article presents ORRN, an Ordinary Differential Equations (ODE)-based recursive image registration network. Our network learns to estimate time-varying voxel velocities for an ODE that models deformation in 4D image data. It adopts a recursive registration strategy to progressively estimate a deformation field through ODE integration of voxel velocities. We evaluate the proposed method on two publicly available lung 4DCT datasets, DIRLab and CREATIS, for two tasks: 1) registering all images to the extreme inhale image for 3D+t deformation tracking and 2) registering extreme exhale to inhale phase images. Our method outperforms other learning-based methods in both tasks, producing the smallest Target Registration Error of 1.24 mm and 1.26 mm, respectively. Additionally, it produces less than 0.001% unrealistic image folding, and the computation speed is less than 1 s for each CT volume. ORRN demonstrates promising registration accuracy, deformation plausibility, and computation efficiency on group-wise and pair-wise registration tasks. It has significant implications in enabling fast and accurate respiratory motion estimation for treatment planning in radiation therapy or robot motion planning in thoracic needle insertion.